What is Risk of Bias?
A bias is a systematic error, or deviation from the truth, in results or inferences. Biases can operate in either direction: different biases can lead to underestimation or overestimation of the true intervention effect.
Zero–risk bias is a tendency to prefer the complete elimination of a risk even when alternative options produce a greater reduction in risk (overall)
Differences in risks of bias can help explain variation in the results of the studies included in a systematic review (i.e. can explain heterogeneity of results). More rigorous studies are more likely to yield results that are closer to the truth. Meta-analysis of results from studies of variable validity can result in false positive conclusions (erroneously concluding an intervention is effective) if the less rigorous studies are biased toward overestimating an intervention’s effect. They might also come to false negative conclusions (erroneously concluding no effect) if the less rigorous studies are biased towards underestimating an intervention’s effect (Detsky 1992).
For all potential sources of bias, it is important to consider the likely magnitude and the likely direction of the bias. For example, if all methodological limitations of studies were expected to bias the results towards a lack of effect, and the evidence indicates that the intervention is effective, then it may be concluded that the intervention is effective even in the presence of these potential biases.
Bias is assessed as a judgement (high, low, or unclear) for individual elements from five domains (selection, performance, attrition, reporting, and other):
Performance bias refers to systematic differences between groups in the care that is provided, or in exposure to factors other than the interventions of interest. . After enrolment into the study, blinding (or masking) of study participants and personnel may reduce the risk that knowledge of which intervention was received, rather than the intervention itself, affects outcomes. Effective blinding can also ensure that the compared groups receive a similar amount of attention, ancillary treatment and diagnostic investigations. Blinding is not always possible, however. For example, it is usually impossible to blind people to whether or not major surgery has been undertaken.
Detection bias refers to systematic differences between groups in how outcomes are determined. Blinding (or masking) of outcome assessors may reduce the risk that knowledge of which intervention was received, rather than the intervention itself, affects outcome measurement. Blinding of outcome assessors can be especially important for assessment of subjective outcomes, such as degree of postoperative pain.
Attrition bias refers to systematic differences between groups in withdrawals from a study. Withdrawals from the study lead to incomplete outcome data. There are two reasons for withdrawals or incomplete outcome data in clinical trials. Exclusions refer to situations in which some participants are omitted from reports of analyses, despite outcome data being available to the trialists. Attrition refers to situations in which outcome data are not available.
Reporting bias refers to systematic differences between reported and unreported findings. Within a published report those analyses with statistically significant differences between intervention groups are more likely to be reported than non-significant differences. This sort of ‘within-study publication bias’ is usually known as outcome reporting bias or selective reporting bias, and may be one of the most substantial biases affecting results from individual studies (Chan 2005).
In addition there are other sources of bias that are relevant only in certain circumstances. These relate mainly to particular trial designs (e.g. carry-over in cross-over trials and recruitment bias in cluster-randomised trials); some can be found across a broad spectrum of trials, but only for specific circumstances (e.g. contamination, whereby the experimental and control interventions get ‘mixed’, for example if participants pool their drugs); and there may be sources of bias that are only found in a particular clinical setting.
Risk of Bias and EA
In Enterprise Architecture Risk Management is a key CSF for Success or failure of a project delivery and ongoing benefit provision.
When doing process reviews for instance, one can easily see how in some instance the choice of reviews participants in a given context can lead to statistical differences in results and therefore produce potentially large deviations from a standardised estimate.
This will in turn leave the EA and other roles concerned with Risk Assessments with a greater risk rather than a properly mitigated one
To Be Continued…